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Title: EM Algorithm for Mapping Quantitative Trait Loci in Multivalent Tetraploids

Author
item LI, JIAHAN - Pennsylvania State University
item DAS, KIRANMOY - Pennsylvania State University
item FU, GUIFANG - Pennsylvania State University
item LIE, YAO - Pennsylvania State University
item Tobias, Christian
item WU, RONGLING - Pennsylvania State University

Submitted to: International Journal of Plant Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/16/2010
Publication Date: 12/15/2010
Citation: Li, J., Das, K., Fu, G., Lie, Y., Tobias, C.M., Wu, R. 2010. EM Algorithm for mapping quantitative trait loci in multivalent tetraploids. International Journal of Plant Genomics. Volume 2010 (2010), Article ID 216547. Available: http://www.hindawi.com/journals/ijpg/2010/216547/.

Interpretive Summary: This work represents a significant advance in techniques used to identify markers for traits in plants with complex polyploid genomes. The mapping method employs the EM algorithm to simultaneously measure the degree of importance a single or multiple genetic loci have on any measured trait as well as accurately identifying the location of the loci given the confounding problem of a genetic mechanism unique to polyploids called double reduction which leads to non-mendelian inheritance in some instances.

Technical Abstract: Multivalent tetraploids that include many plant species, such as potato, sugarcane and rose, are of paramount importance to agricultural production and biological research. Quantitative trait locus (QTL) mapping in multivalent tetraploids is challenged by their unique cytogenetic properties, such as double reduction. We develop a statistical method for mapping multivalent tetraploid QTLs by considering these cytogenetic properties. This method is built in the mixture model-based framework and implemented with the EM algorithm. The method allows the simultaneous estimation of QTL positions, QTL effects, the chromosomal pairing factor and the degree of double reduction as well as the assessment of the estimation precision of these parameters. We used simulated data to examine the statistical properties of the method and validate its utilization. The new method and its software will provide a useful tool for QTL mapping in multivalent tetraploids that undergo double reduction.